| Literature DB >> 36203018 |
Ross D Markello1, Justine Y Hansen1, Zhen-Qi Liu1, Vincent Bazinet1, Golia Shafiei1, Laura E Suárez1, Nadia Blostein2, Jakob Seidlitz3, Sylvain Baillet1, Theodore D Satterthwaite3, M Mallar Chakravarty2, Armin Raznahan4, Bratislav Misic5.
Abstract
Imaging technologies are increasingly used to generate high-resolution reference maps of brain structure and function. Comparing experimentally generated maps to these reference maps facilitates cross-disciplinary scientific discovery. Although recent data sharing initiatives increase the accessibility of brain maps, data are often shared in disparate coordinate systems, precluding systematic and accurate comparisons. Here we introduce neuromaps, a toolbox for accessing, transforming and analyzing structural and functional brain annotations. We implement functionalities for generating high-quality transformations between four standard coordinate systems. The toolbox includes curated reference maps and biological ontologies of the human brain, such as molecular, microstructural, electrophysiological, developmental and functional ontologies. Robust quantitative assessment of map-to-map similarity is enabled via a suite of spatial autocorrelation-preserving null models. neuromaps combines open-access data with transparent functionality for standardizing and comparing brain maps, providing a systematic workflow for comprehensive structural and functional annotation enrichment analysis of the human brain.Entities:
Year: 2022 PMID: 36203018 DOI: 10.1038/s41592-022-01625-w
Source DB: PubMed Journal: Nat Methods ISSN: 1548-7091 Impact factor: 47.990